Talk: Integrating Learning with Game Theory for Societal Challenges

Jun 5 2019 - 11:00am to 1:00pm
2-260 Keller Hall

Abstract: There is a rising interest in developing artificial
intelligence-based tools to address challenges in various security domains,
e.g., protecting critical infrastructure and cyber networks and protecting
wildlife, fishery, and forest. Motivated by these challenges, we have
proposed game theory and machine learning based models and algorithms for
problems with strategic interactions among agents. In this talk, I will
introduce our models and algorithms that have led to two successfully
deploy applications: one used by US Coast Guard for protecting the Staten
Island Ferry in New York City since April 2013, the other used in multiple
conservation areas around the world for anti-poaching effort. In addition,
I will highlight our most recent advances in integrating deep learning with
game theory, including computing equilibrium by learning from self-play and
end-to-end learning of game parameters.

Bio: Fei Fang is an Assistant Professor at the Institute for Software
Research in the School of Computer Science at Carnegie Mellon University.
Before joining CMU, she was a Postdoctoral Fellow at the Center for
Research on Computation and Society (CRCS) at Harvard University. She
received her Ph.D. from the Department of Computer Science at the
University of Southern California in June 2016. She received her bachelor
degree from the Department of Electronic Engineering, Tsinghua University
in July 2011. Her research lies in the field of artificial intelligence and
multi-agent systems, focusing on integrating game theory and mechanism
design with machine learning. Her work has been motivated by and applied to
security, sustainability, and mobility domains, contributing to the theme
of AI for Social Good.